Determinants of the Efficacy of Cardiac Ischemic Preconditioning:A Systematic Review and Meta-Analysis of Animal Studies

Contains fulltext : 152112.PDF (publisher's version ) (Open Access)BACKGROUND: Ischemic preconditioning (IPC) of the heart is a protective strategy in which a brief ischemic stimulus immediately before a lethal ischemic episode potently limits infarct size. Although very promising in animal models of myocardial infarction, IPC has not yet been successfully translated to benefit for patients. OBJECTIVE: To appraise all preclinical evidence on IPC for myocardial infarction and identify factors hampering translation. METHODS AND RESULTS: Using systematic review and meta-analysis, we identified 503 animal studies reporting infarct size data from 785 comparisons between IPC-treated and control animals. Overall, IPC reduced myocardial infarction by 24.6% [95%CI 23.5, 25.6]. Subgroup analysis showed that IPC efficacy was reduced in comorbid animals and non-rodents. Efficacy was highest in studies using 2-3 IPC cycles applied <45 minutes before myocardial infarction. Local and remote IPC were equally effective. Reporting of study quality indicators was low: randomization, blinding and a sample size calculation were reported in 49%, 11% and 2% of publications, respectively. CONCLUSIONS: Translation of IPC to the clinical setting may be hampered by the observed differences between the animals used in preclinical IPC studies and the patient population, regarding comorbidity, sex and age. Furthermore, the IPC protocols currently used in clinical trials could be optimized in terms of timing and the number of ischemic cycles applied. In order to inform future clinical trials successfully, future preclinical studies on IPC should aim to maximize both internal and external validity, since poor methodological quality may limit the value of the preclinical evidence

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases

Impact of animal characteristics on IPC efficacy.

<p>Data are presented as raw difference in means (MD) in infarct size as a percentage of the area at risk (IS/AAR%). Horizontal white line and grey bar represent the pooled effect estimate and its 95% confidence interval. The number of comparisons contributing data is indicated in each bar. *differs from dog; **differs from rat; ^#differs from total conditions; ^##differs from all other groups.</p

Reporting of study quality indicators and risk of bias in 503 included studies.

<p><b>A</b>, Reporting of three key study quality indicators was found to be poor in many cases. <b>B</b>, Using SYRCLE's risk of bias tool, the risks of selection, performance, detection, attrition and other biases were assessed. Lack of (adequate) reporting of measures to reduce bias resulted in a high percentage of unclear risk of bias for most items.</p

Flow chart of the study selection process.

<p>A systematic search in PubMed and EMBASE yielded 6237 unique publications. After application of inclusion and exclusion criteria, data from 503 publications were included in the meta-analysis and quality assessment.</p

Meta-analysis animal model and IPC characteristics.

<p>Meta-analysis animal model and IPC characteristics.</p

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications.

Acknowledgements: This work was supported by funding from the European and American Thyroid Associations, the Erasmus University Rotterdam, the Dutch Organization for Scientific Research (NWO) (M.Med.), and the NIH (grants R35GM118335 and T32DK110966). Acknowledgments and study-specific acknowledgments are provided in the Supplementary Note. We conducted this research using the UK Biobank resource under the application numbers 53723 and 20272.Funder: This work was supported by funding from the European and American Thyroid Associations, the Erasmus University Rotterdam, and the Dutch Organization for Scientific Research (NWO).To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases